In the rapidly evolving landscape of AI and analytics, the importance of a robust architecture cannot be overstated. As businesses increasingly rely on data-driven insights and AI-powered solutions, the underlying infrastructure that supports these technologies becomes a critical factor in their success. Recently, a panel of experts gathered to discuss architecture's pivotal role in AI and analytics, sharing insights on business drivers, common pitfalls, and innovative solutions.
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Compliance and Privacy Concerns
Andrew Madson from Dremio highlighted the challenge of balancing AI implementation with regulatory compliance: "If we build AI on top of our data platform, but we don't have some kind of mechanism to pop these folks out, which is their right, it's incredibly hard to go back and fix that on the back end." Architectures must be designed with privacy and compliance in mind from the outset.
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Read the full story, via DZone.
